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A nifH-based Oligonucleotide Microarray for Functional Diagnostics of Nitrogen-fixing Microorganisms.

Zhang L, Hurek T, Reinhold-Hurek B

Laboratory of General Microbiology, Center of Applied Gene Sensoric (CAG), University of Bremen, P.O. Box 33 04 40, D-28334, Bremen, Germany, breinhold@uni-bremen.de.

Nitrogen fixation is an important process in biogeochemical cycles exclusively carried out by prokaryotes, mostly by an evolutionarily conserved nitrogenase protein complex, of which one of the structural genes (nifH) is highly valuable for phylogenetic and diversity analyses. We developed a nifH-based short oligonucleotide microarray (nifH diagnostic microarray) as a rapid tool to effectively monitor nitrogen-fixing diazotrophic populations in a wide range of environments. Taking account of the overwhelming predominance of environmental nifH fragments from uncultivated microorganisms in public databases, our nifH microarray is mainly based on nifH sequences from as yet unidentified prokaryotes. Standard conditions for microarray performance were determined, and criteria for the design of specific oligonucleotides were defined. A primary set of 56 oligonucleotides was validated with fluorescence-labeled single-stranded nifH targets from five reference strains, 26 environmental clones, and artificial mixtures of reference strains. The nifH microarray was applied to analyze the diversity (based on DNA) and activity (based on mRNA) of diazotrophs in roots of wild rice samples from Namibia. Results demonstrated that only a small subset of diazotrophs being present in the sample were actually fixing nitrogen actively. Our data suggest that the developed nifH microarray is a highly reproducible and semiquantitative method for mapping the variability of diazotrophic diversity, allowing rapid comparisons of the relative abundance and activity of diazotrophic prokaryotes in the environment. A further refined nifH microarray comprising of 194 oligonucleotide probes now covers more than 90% of sequences in our nifH database.

Published 11 January 2007 in Microb Ecol.
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The Analysis of Gene Expression Data